Journal of Diabetes Science and Technology最新文献

{"title":"Psychosocial and Glycemic Benefits for Insulin-Using Adults With Type 2 Diabetes After Six Months of Pump Therapy: A Quasi-Experimental Approach.","authors":"William H Polonsky, Emily C Soriano","doi":"10.1177/19322968231198533","DOIUrl":"10.1177/19322968231198533","url":null,"abstract":"<p><strong>Background: </strong>Continuous subcutaneous insulin infusion (CSII) use in adults with type 1 diabetes offers psychosocial and clinical benefits, but little is known about its impact on such outcomes in the type 2 diabetes (T2D) population. To address this gap, we conducted a quasi-experimental prospective study to assess psychosocial, glycemic, and behavioral changes over six months in T2D adults on multiple daily injections (MDI) who were interested in starting Omnipod DASH, comparing those who did versus did not start on it.</p><p><strong>Methods: </strong>In total, 458 adults with T2D completed baseline questionnaires assessing psychosocial dimensions (eg, diabetes distress), clinical metrics (eg, HbA_1c [glycosylated hemoglobin]), and behavioral measures (eg, missed mealtime boluses). Six months later, 220 (48.0%) completed the same questionnaire again. To examine differences in outcomes over time between those who began CSII (n = 176) versus those who remained on MDI (n = 44), a latent change score approach was used.</p><p><strong>Results: </strong>The CSII users reported greater gains than MDI users on all major psychosocial metrics, including overall well-being (<i>P</i> < .001) diabetes distress (<i>P</i> < .001), perceived T2D impact on quality of life (<i>P</i> = .003), and hypoglycemic worries and concerns (<i>P</i> < .001). The CSII users similarly reported a larger decline in HbA_1c than MDI users (<i>P</i> < .05) and greater declines in two critical self-care behaviors: number of missed mealtime boluses (<i>P</i> < .001) and number of days of perceived overeating (<i>P</i> = .001).</p><p><strong>Conclusions: </strong>The introduction of CSII (Omnipod DASH) in T2D adults can contribute to significant psychosocial, glycemic, and behavioral benefits, indicating that broader use of CSII in the T2D population may be of value.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"758-768"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035139/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10155297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ketone-Based Alert System for Insulin Pump Failures.","authors":"Eleonora M Aiello, Lori M Laffel, Mary-Elizabeth Patti, Francis J Doyle","doi":"10.1177/19322968231209339","DOIUrl":"10.1177/19322968231209339","url":null,"abstract":"<p><strong>Background: </strong>An increasing number of individuals with type 1 diabetes (T1D) manage glycemia with insulin pumps containing short-acting insulin. If insulin delivery is interrupted for even a few hours due to pump or infusion site malfunction, the resulting insulin deficiency can rapidly initiate ketogenesis and diabetic ketoacidosis (DKA).</p><p><strong>Methods: </strong>To detect an event of accidental cessation of insulin delivery, we propose the design of ketone-based alert system (K-AS). This system relies on an extended Kalman filter based on plasma 3-beta-hydroxybutyrate (BOHB) measurements to estimate the disturbance acting on the insulin infusion/injection input. The alert system is based on a novel physiological model capable of simulating the ketone body turnover in response to a change in plasma insulin levels. Simulated plasma BOHB levels were compared with plasma BOHB levels available in the literature. We evaluated the performance of the K-AS on 10 in silico subjects using the S2014 UVA/Padova simulator for two different scenarios.</p><p><strong>Results: </strong>The K-AS achieves an average detection time of 84 and 55.5 minutes in fasting and postprandial conditions, respectively, which compares favorably and improves against a detection time of 193 and 120 minutes, respectively, based on the current guidelines.</p><p><strong>Conclusions: </strong>The K-AS leverages the rapid rate of increase of plasma BOHB to achieve short detection time in order to prevent BOHB levels from rising to dangerous levels, without any false-positive alarms. Moreover, the proposed novel insulin-BOHB model will allow us to understand the efficacy of treatment without compromising patient safety.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"683-691"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72014421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensor-Assisted Wound Therapy in Plantar Diabetic Foot Ulcer Treatment: A Randomized Clinical Trial.","authors":"Dirk Hochlenert, Can Bogoclu, Kevin Cremanns, Lars Gierschner, Dominik Ludmann, Mira Mertens, Timo Tromp, Annika Weggen, Hubert Otten","doi":"10.1177/19322968231213095","DOIUrl":"10.1177/19322968231213095","url":null,"abstract":"<p><strong>Background: </strong>Offloading is the cornerstone of treatment of plantar diabetic foot ulcers. It limits mobility with consequent psychological and cardiovascular side effects, and if devices are removed, healing is delayed.</p><p><strong>Methods: </strong>We developed three non-removable techniques with increasing offloading potential (multilayer felt sole, felt-fiberglass sole, or total contact casts with ventral windows) and sensors built within. Smartwatch and web apps displayed pressure, temperature, humidity, and steps. They alerted patients, staff, and a telemedicine center when pressure limits (125 kPa) were exceeded. Patients were advised to walk as much as they had done before the ulcer episode. To evaluate the potential of this intervention, we enrolled 20 ambulatory patients in a randomized clinical trial. The control group used the same offloading and monitoring system, but neither patients nor therapists received any information or warnings.</p><p><strong>Results: </strong>Three patients withdrew consent. The median time to healing of ulcers was significantly shorter in the intervention group compared with controls, 40.5 (95% confidence interval [CI] = 28-not applicable [NA]) versus 266.0 (95% CI = 179-NA) days (<i>P</i> = .037), and increasing ulcer area was observed less frequently during study visits (7.9% vs 29.7%, <i>P</i> = .033). A reduction of wound area by 50% was reached at a median of 10.2 (95% CI = 7.25-NA) versus 19.1 (95% CI = 13.36-NA) days (<i>P</i> = .2). Participants walked an average of 1875 (SD = 1590) steps per day in intervention group and 1806 (SD = 1391) in the control group.</p><p><strong>Conclusions: </strong>Sensor-assisted wound therapy may allow rapid closure of plantar foot ulcers while maintaining patient's mobility during ulcer therapy.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"692-698"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035378/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138434119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"py-mgipsim: An Open-Source Python Library for Simulating Type 1 Diabetes With Diverse Meals and Physical Activities.","authors":"Mate Siket, Mudassir M Rashid, Ali Cinar","doi":"10.1177/19322968251328664","DOIUrl":"10.1177/19322968251328664","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"855-856"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926810/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143663523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to \"Time to Moderate and Severe Hyperglycemia and Ketonemia Following an Insulin Pump Occlusion\".","authors":"","doi":"10.1177/19322968251325907","DOIUrl":"10.1177/19322968251325907","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"862"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11907488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143624927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Three-Step Data-Driven Methodology to Assess Adherence to Basal Insulin Therapy in Patients With Insulin-Treated Type 2 Diabetes.","authors":"Jannie Toft Damsgaard Nørlev, Thomas Kronborg, Morten Hasselstrøm Jensen, Peter Vestergaard, Ole Hejlesen, Stine Hangaard","doi":"10.1177/19322968231222007","DOIUrl":"10.1177/19322968231222007","url":null,"abstract":"<p><strong>Background: </strong>While health care providers (HCPs) are generally aware of the challenges concerning insulin adherence in adults with insulin-treated type 2 diabetes (T2D), data guiding identification of insulin nonadherence and understanding of injection patterns have been limited. Hence, the aim of this study was to examine detailed injection data and provide methods for assessing different aspects of basal insulin adherence.</p><p><strong>Method: </strong>Basal insulin data recorded by a connected insulin pen and prescribed doses were collected from 103 insulin-treated patients (aged ≥18 years) with T2D from an ongoing clinical trial (NCT04981808). We categorized the data and analyzed distributions of correct doses, increased doses, reduced doses, and missed doses to quantify adherence. We developed a three-step model evaluating three aspects of adherence (overall adherence, adherence distribution, and dose deviation) offering HCPs a comprehensive assessment approach.</p><p><strong>Results: </strong>We used data from a connected insulin pen to exemplify the use of the three-step model to evaluate overall, adherence, adherence distribution, and dose deviation using patient cases.</p><p><strong>Conclusion: </strong>The methodology provides HCPs with detailed access to previously limited clinical data on insulin administration, making it possible to identify specific nonadherence behavior which will guide patient-HCP discussions and potentially provide valuable insights for tailoring the most appropriate forms of support.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"749-757"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035273/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139074252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy Concerns Related to Data Sharing for European Diabetes Devices.","authors":"Pietro Randine, Matthias Pocs, John Graham Cooper, Dimitrios Tsolovos, Miroslav Muzny, Rouven Besters, Eirik Årsand","doi":"10.1177/19322968231210548","DOIUrl":"10.1177/19322968231210548","url":null,"abstract":"<p><strong>Background: </strong>Individuals with diabetes rely on medical equipment (eg, continuous glucose monitoring (CGM), hybrid closed-loop systems) and mobile applications to manage their condition, providing valuable data to health care providers. Data sharing from this equipment is regulated via Terms of Service (ToS) and Privacy Policy documents. The introduction of the Medical Devices Regulation (MDR) and In Vitro Diagnostic Medical Devices Regulation (IVDR) in the European Union has established updated rules for medical devices, including software.</p><p><strong>Objective: </strong>This study examines how data sharing is regulated by the ToS and Privacy Policy documents of approved diabetes medical equipment and associated software. It focuses on the equipment approved by the Norwegian Regional Health Authorities.</p><p><strong>Methods: </strong>A document analysis was conducted on the ToS and Privacy Policy documents of diabetes medical equipment and software applications approved in Norway.</p><p><strong>Results: </strong>The analysis identified 11 medical equipment and 12 software applications used for diabetes data transfer and analysis in Norway. Only 3 medical equipment (OmniPod Dash, Accu-Chek Insight, and Accu-Chek Solo) were registered in the European Database on Medical Devices (EUDAMED) database, whereas none of their respective software applications were registered. Compliance with General Data Protection Regulation (GDPR) security requirements varied, with some software relying on adequacy decisions (8/12), whereas others did not (4/12).</p><p><strong>Conclusions: </strong>The study highlights the dominance of non-European Economic Area (EEA) companies in medical device technology development. It also identifies the lack of registration for medical equipment and software in the EUDAMED database, which is currently not mandatory. These findings underscore the need for further attention to ensure regulatory compliance and improve data-sharing practices in the context of diabetes management.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"611-619"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035141/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92154381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Continuous Glucose Monitoring Values for Bolus Size Calculation in Smart Multiple Daily Injection Systems: No Negative Impact on Post-bolus Glycemic Outcomes Found in Real-World Data.","authors":"Franck Diaz-Garelli, Aakash Shah, Arthur Mikhno, Pratik Agrawal, Amanda Kinnischtzke, Robert A Vigersky","doi":"10.1177/19322968231202803","DOIUrl":"10.1177/19322968231202803","url":null,"abstract":"<p><strong>Background: </strong>Recent evidence shows that it may be safe to estimate bolus sizes based on continuous glucose monitoring (CGM) rather than blood glucose (BG) values using glycemic trend-adjusted bolus calculators. Users may already be doing this in the real world, though it is unclear whether this is safe or effective for calculators not employing trend adjustment.</p><p><strong>Methods: </strong>We assessed real-world data from a smart multiple daily injections (MDIs) device users with a CGM system, hypothesizing that four-hour post-bolus outcomes using CGM values are not inferior to those using BG values. Our data set included 184 users and spanned 18 months with 79 000 bolus observations. We tested differences using logistic regression predicting CGM or BG value usage based on outcomes and confirmed initial results using a mixed model regression accounting for within-subject correlations.</p><p><strong>Results: </strong>Comparing four-hour outcomes for bolus events using CGM and BG values revealed no differences using our initial approach (<i>P</i> > .183). This finding was confirmed by our mixed model regression approach in all cases (<i>P</i> > .199), except for times below range outcomes. Higher times below range were predictive of lower odds of CGM-based bolus calculations (OR = 0.987, <i>P</i> < .0001 and OR = 0.987, <i>P</i> = .0276, for time below 70 and 54 mg/dL, respectively).</p><p><strong>Conclusions: </strong>We found no differences in four-hour post-bolus glycemic outcomes when using CGM or BG except for time below range, which showed evidence of being lower for CGM. Though preliminary, our results confirm prior findings showing non-inferiority of using CGM values for bolus calculation compared with BG usage in the real world.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"642-648"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12035321/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41097861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of Continuous Glucose Monitoring in People With Type 1 Diabetes Receiving Hemodialysis in Hospital.","authors":"Ray Wang, Mervyn Kyi, Brintha Krishnamoorthi, Ailie Connell, Cherie Chiang, Debra Renouf, Rahul Barmanray, Karen Dwyer, Spiros Fourlanos","doi":"10.1177/19322968251318758","DOIUrl":"10.1177/19322968251318758","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"859-861"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11830158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143414397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Transition From Multiple Daily Injection Therapy to Automated Insulin Delivery in People With Type 1 Diabetes and Limited Diabetes Self-Management.","authors":"Mette J Nitschke, Maria H Hemmingsen, Hanne H Nørgaard, Kristina A Robak, Pia Nørrevang, Merete M Andersen, Thomas F Dejgaard, Ulrik Pedersen-Bjergaard, Peter L Kristensen","doi":"10.1177/19322968251315184","DOIUrl":"10.1177/19322968251315184","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"857-858"},"PeriodicalIF":4.1,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11760064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143038958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}